Difan Zou

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Quanquan GuAssociate Professor of Computer Science, UCLAAdresă de e-mail confirmată pe cs.ucla.edu
Zhengyuan XuUniversity of Science and Technology of ChinaAdresă de e-mail confirmată pe ustc.edu.cn
Yuan CaoThe University of Hong KongAdresă de e-mail confirmată pe hku.hk
Pan XuDuke UniversityAdresă de e-mail confirmată pe duke.edu
Jingfeng WuUniversity of California, BerkeleyAdresă de e-mail confirmată pe berkeley.edu
Vladimir BravermanProfessor of Computer Science, Johns Hopkins University; Google Research; Adjunct Professor, Rice U.Adresă de e-mail confirmată pe cs.jhu.edu
Sham M KakadeHarvard UniversityAdresă de e-mail confirmată pe seas.harvard.edu
Dongruo ZhouIndiana University BloomingtonAdresă de e-mail confirmată pe iu.edu
Jinghui ChenAssistant Professor of Information Sciences and Technology, Penn State UniversityAdresă de e-mail confirmată pe psu.edu
Yizhou SunProfessor, Computer Science, UCLAAdresă de e-mail confirmată pe cs.ucla.edu
Ziniu HuxAIAdresă de e-mail confirmată pe caltech.edu
Yuanzhi LiAssistant Professor at CMUAdresă de e-mail confirmată pe andrew.cmu.edu
Spencer FreiGoogle DeepMindAdresă de e-mail confirmată pe google.com
Zhimeng JiangGoogle, TAMUAdresă de e-mail confirmată pe google.com
Guanchu WangRice UniversityAdresă de e-mail confirmată pe rice.edu
S osherAdresă de e-mail confirmată pe math.ucla.edu
Yaodong YuUniversity of California, BerkeleyAdresă de e-mail confirmată pe berkeley.edu
L HanzoChair of Telecommunications, University of SouthamptonAdresă de e-mail confirmată pe ecs.soton.ac.uk

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Difan Zou

The University of Hong Kong

Adresă de e-mail confirmată pe cs.hku.hk - Pagina de pornire

Machine Learning Deep Learning Optimization Stochastic Algorithms Signal Processing


Titlu Sortați după descrierea bibliografică Sortați după an Sortați după titlu	Citat de Citat de	Anul
Improving adversarial robustness requires revisiting misclassified examples Y Wang, D Zou, J Yi, J Bailey, X Ma, Q Gu International conference on learning representations, 2019	866	2019
Gradient descent optimizes over-parameterized deep ReLU networks D Zou, Y Cao, D Zhou, Q Gu Machine learning 109, 467-492, 2020	789	2020
Layer-dependent importance sampling for training deep and large graph convolutional networks D Zou, Z Hu, Y Wang, S Jiang, Y Sun, Q Gu Advances in neural information processing systems 32, 2019	368	2019
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ... Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022	336*	2022
An improved analysis of training over-parameterized deep neural networks D Zou, Q Gu NeurIPS 2018, 2019	285	2019
Global convergence of Langevin dynamics based algorithms for nonconvex optimization P Xu, J Chen, D Zou, Q Gu Advances in Neural Information Processing Systems 31, 2018	238	2018
Ensemble forecasts of coronavirus disease 2019 (COVID-19) in the US EL Ray, N Wattanachit, J Niemi, AH Kanji, K House, EY Cramer, J Bracher, ... MedRXiv, 2020.08. 19.20177493, 2020	224	2020
How much over-parameterization is sufficient to learn deep ReLU networks? Z Chen, Y Cao, D Zou, Q Gu arXiv preprint arXiv:1911.12360, 2019	149	2019
Epidemic model guided machine learning for COVID-19 forecasts in the United States D Zou, L Wang, P Xu, J Chen, W Zhang, Q Gu MedRxiv, 2020.05. 24.20111989, 2020	125	2020
The United States COVID-19 forecast hub dataset EY Cramer, Y Huang, Y Wang, EL Ray, M Cornell, J Bracher, A Brennen, ... Scientific data 9 (1), 462, 2022	116	2022
A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave J Bracher, D Wolffram, J Deuschel, K Görgen, JL Ketterer, A Ullrich, ... Nature communications 12 (1), 5173, 2021	92*	2021
Benign overfitting of constant-stepsize sgd for linear regression D Zou, J Wu, V Braverman, Q Gu, S Kakade Conference on Learning Theory, 4633-4635, 2021	77	2021
A 1Mbps real-time NLOS UV scattering communication system with receiver diversity over 1km G Wang, K Wang, C Gong, D Zou, Z Jiang, Z Xu IEEE Photonics Journal 10 (2), 1-13, 2018	72	2018
How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression? J Wu, D Zou, Z Chen, V Braverman, Q Gu, PL Bartlett ICLR 2024, 2024	65	2024
Information security risks outside the laser beam in terrestrial free-space optical communication D Zou, Z Xu IEEE photonics journal 8 (5), 1-9, 2016	62	2016
Understanding the generalization of adam in learning neural networks with proper regularization D Zou, Y Cao, Y Li, Q Gu ICLR 2023, 2023	60	2023
Faster convergence of stochastic gradient langevin dynamics for non-log-concave sampling D Zou, P Xu, Q Gu Uncertainty in Artificial Intelligence, 1152-1162, 2021	51	2021
Multiple models for outbreak decision support in the face of uncertainty K Shea, RK Borchering, WJM Probert, E Howerton, TL Bogich, SL Li, ... Proceedings of the National Academy of Sciences 120 (18), e2207537120, 2023	48*	2023
Characterization on practical photon counting receiver in optical scattering communication D Zou, C Gong, K Wang, Z Xu IEEE Transactions on Communications 67 (3), 2203-2217, 2018	48	2018
Non-line-of-sight scattering channel modeling for underwater optical wireless communication W Liu, D Zou, Z Xu, J Yu 2015 IEEE International Conference on Cyber Technology in Automation …, 2015	48	2015

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